• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.57-62
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• 2002

The semiconductor industry has continuously been looking for the ways to improve yield and to reduce manufacturing cost. The layout modification approach, one of yield enhancement techniques, is applicable to all design styles, but it does not require any additional resources in terms of silicon area. The layout modification method for yield enhancement consists of making local variations in the layout of some layers in such a way that the critical area, and consequently the sensitivity of the layer to point defects, is reduced. Chen and Koren (1995) proposed a greedy algorithm that removes defect sensitive area using via moving, but it is easy to fall into a local minimum. In this paper, we present a via moving algorithm using simulated annealing and enhance yield by diminishing defect sensitive area. As a result, we could decrease the defect sensitive area effectively compared to the greedy algorithm presented by Chen and Koren. We expect that the proposed algorithm can make significant contributions on company profit through yield enhancement.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.33-44
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• 2012

A class of recurrent neural networks is proposed and proven to be capable of identifying any discrete-time dynamical system. The applications of the proposed network are addressed in the encoding, identification, and extraction of finite state automata. Simulation results show that the identification of finite state automata using the proposed network, trained by the hybrid greedy simulated annealing with a modified error function in the learning stage, exhibits generally better performance than other conventional identification schemes.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.98-105
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• 2009

In this paper, new data centric storage that is dynamically adapted to the change of work load is proposed. The proposed data centric storage distributes the load of hot spot area by using multilevel grid technique. Also, the proposed method is able to use existing routing protocol such as GPSR (Greedy Perimeter Stateless Routing) with small changes. Through simulation the proposed method enhances the lifetime of sensor networks over one of the state-of-the-art data centric storages. We implement the proposed method based on a operating system for sensor networks, and evaluate the performance through running based on a simulation tool.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.157-161
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• 2010

Vehicular Ad-hoc NETworks (VANETs) suffer from frequent network disconnections due to obstacles such as buildings even in urban environments with high density of traffic. Thus, in this paper, we propose a routing algorithm that finds optimal end-to-end paths in terms of both traffic density and distance in the urban VANET and selects the next hop with the minimum distance, while maintaining the minimum hop counts over the path. The simulation results show that the proposed algorithm achieves higher throughput and smaller end-to-end delay than Greedy Perimeter Stateless Routing (GPSR) with message carrying.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.237-244
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• 2007

In this paper we investigate the benefits of a data aggregation to prolong the lifetime of wireless sensor networks. To reduce the overload of messages from source node to sink node, data aggregation technique is generally used at intermediate node in path. The DD-G(Directed Diffusion-Greedy) can diminish the consumption of node energy by establishing energy effective single path from source to destination. In this case, the nodes near sink node have some problems, i) overly concentration of energy consumption, ii) increase of message delay time. To solve these problems, we propose a new data aggregation method which consider distribution of network overload, especially at the nodes close to sink node. The result shows that it can save energy and network delay time.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.300-307
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• 2008

Power management (PM) depends on the power state transition and system workload. The system model is composed of corresponding stochastic models of the power state and system queue. In this paper, stochastic models which can handle various PM techniques are developed. SRN (Stochastic Reward Nets), an extended Petri-Net, has facilities that represent system queue and various modelling functions. The SRN is employed for developing PM models. An adaptive timeout PM model is also introduced and the power consumption and performance of this model are compared with other existing PM techniques models such as greedy and N-Policy techniques.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.33-38
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• 2014

This paper investigates the shaping operation problem introduced by Callahan et al., namely the k-fragility maximization problem (k-FMP), whose goal is to find a subset of personals within a terrorist group such that the regeneration capability of the residual group without the personals is minimized. To improve the impact of the shaping operation, the degree centrality of the residual graph needs to be maximized. In this paper, we propose a new greedy algorithm for k-FMP. We discover some interesting discrete properties and use this to design a more thorough greedy algorithm for k-FMP. Our simulation result shows that the proposed algorithm outperforms Callahan et al.'s algorithm in terms of maximizing degree centrality. While our algorithm incurs higher running time (factor of k), given that the applications of the problem is expected to allow sufficient amount of time for thorough computation and k is expected to be much smaller than the size of input graph in reality, our algorithm has a better merit in practice.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.8
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• pp.768-772
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• 2008

Today's microprocessor normally includes several processing cores to reduce the energy consumption without losing performance. In this paper, data transfer ordering mechanism can be efficiently used for cache coherence solution in unidirectional ring interconnect. RING-DATA ORDER combines the simplicity of GREEDY-ORDER and the performance of RING-ORDER. RING-DATA ORDER can be easily applicable to multicore processor with unidirectional ring interconnect.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.294-304
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• 2011

Enhancing continuous queries over data streams with temporal functions and predicates enriches the expressive power of those queries. While traditional continuous queries retrieve only the values of attributes, temporal continuous queries retrieve the valid time intervals of those values as well. Correctly evaluating such queries requires the coalescing of adjacent timestamps for value-equivalent tuples prior to evaluating temporal functions and predicates. For many stream applications, the available computing resources may be too limited to produce exact query results. These limitations are commonly addressed through load shedding and produce approximated query results. There have been many load shedding mechanisms proposed so far, but for temporal continuous queries, the presence of coalescing makes theses existing methods unsuitable. In this paper, we propose a new accuracy metric and load shedding algorithm that are suitable for temporal query processing when memory is insufficient. The accuracy metric uses a combination of the Jaccard coefficient to measure the accuracy of attribute values and $\mathcal{PQI}$ interval orders to measure the accuracy of the valid time intervals in the approximate query result. The algorithm employs a greedy strategy combining two objectives reflecting the two accuracy metrics (i.e., value and interval). In the performance study, the proposed greedy algorithm outperforms a conventional random load shedding algorithm by up to an order of magnitude in its achieved accuracy.

• Journal of IKEEE
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• v.17 no.3
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• pp.339-345
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• 2013

In this paper, the probabilistic exclusion based orthogonal matching pursuit (PEOMP) algorithm for the sparse signal reconstruction is proposed. Some of recent greedy algorithms such as CoSaMP, gOMP, BAOMP improved the reconstruction performance by deleting unsuitable atoms at each iteration. They still often fail to converge to the solution because the support set could not escape from a local minimum. PEOMP helps to escape by excluding a random atom in the support set according to a well-chosen probability function. Experimental results show that PEOMP outperforms several OMP based algorithms and the $l_1$ optimization method in terms of exact reconstruction probability.